Visual Senses of “Online Learning” and “Instructional Design”: Social Imagery as Online Learning Data

Introduction

In the online learning data space, it is important to understand the concepts, ideas, personages, and other phenomena through multiple means, including through “social imagery,” the images shared on social media from content-sharing social media sites, websites, and the Social Web (Web 2.0). To explore how this might work, two social image sets were collected through Google Image Search around the generalist term “online learning” and the pseudo-related term “instructional design.” (“Instructional design” enables “online learning.” “Instructional design” supports “online learning.” “Online learning” requires “instructional design.” “Online learning” benefits from “instructional design.”)

To preview what some of this might look like, a search for “online learning data” was run with the same approaches described above (Figures 1 and 2). It helps to do a walk-through of the images to set an initial baseline. In terms of some of the image types in this set, there are stock imagery, slideshow slides, stylized images, data tables, informational graphics, logos, glyphs, website banners, mobile device images and mock-ups, diagrams, flowcharts, data stories (with photos, timelines, images, and text), digital drawings, composite images (a mixed set of image types in a grid layout), geographical maps (including choropleth ones), screenshots, and others. Content-wise, there are people depicted in various learning activities, book covers, academic models, digital games, work flowcharts, data visualizations, software details, and others. Some images are clearly stock imagery—with stylized gloss, proportionality, professional lighting, focus, depth of field, and other elements; the messaging is coherent, and non-messages are controlled for to avoid muddying the message. An initial perusal suggests that these images come from online courses, brochures, books, ads, branding endeavors, jokes, and blogs. The decorative images make the typical plays on the 0’s and 1’s, and they also include node-link diagrams. These images give a sense of slice-in-time and contemporaneous present-ness because of some of the recent-ness of the contents. There is also noise in the image set in that “online learning data” was not truly represented in all the surfaced disaggregated images. Cleaning this dataset would require removing non-relevant images, but that curation may also remove some potentially relevant details (which may be non-obvious until the time of the analysis). There does almost always seem to be a gap between a “text search” and the visual multi-dimensionality of image data. The Google Search – Image tags (used for filtering) were as follows: analytics, analysis, survival analysis, cont, possible, graph, using, event, innovative, symposium, survey, time, learner, batch, some, and visual.

Figure 1.

Screenshot of “online learning data” imagery from Google Search (on the web)

Figure 2.

Screenshot of “online learning data” imagery from Google Search (on the computer)

While prior work has included coding social imagery to particular themes (Hai-Jew, 2018), this work goes beyond descriptors. Rather, this work explores a simple hypothesis based on the idea that social imagery is part of strategic messaging to particular target audiences of interest. More specifically, this work hypothesizes two assertions:

• Hypothesis 1: “Online learning” social imagery will be aimed at potential and continuing learners to encourage their participation in online learning.

• Hypothesis 2: “Instructional design” social imagery will be aimed at two audiences: (1) practitioners and would-be practitioners, and (2) administrators and executives who might hire instructional designers or commission outside ID work.